The CO Luminosity Density at High-z (COLDz) Survey: A Sensitive, Large-area Blind Search for Low-J CO Emission from Cold Gas in the Early Universe with the Karl G. Jansky Very Large Array
Bibliographic record
Abstract
Abstract We describe the CO Luminosity Density at High-z (COLDz) survey, the first spectral line deep field targeting CO(1–0) emission from galaxies at z = 1.95–2.85 and CO(2–1) at z = 4.91–6.70. The main goal of COLDz is to constrain the cosmic density of molecular gas at the peak epoch of cosmic star formation. By targeting both a wide (∼51 arcmin2) and a deep (∼9 arcmin2) area, the survey is designed to robustly constrain the bright end and the characteristic luminosity of the CO(1–0) luminosity function. An extensive analysis of the reliability of our line candidates and new techniques provide detailed completeness and statistical corrections as necessary to determine the best constraints to date on the CO luminosity function. Our blind search for CO(1–0) uniformly selects starbursts and massive main-sequence galaxies based on their cold molecular gas masses. Our search also detects CO(2–1) line emission from optically dark, dusty star-forming galaxies at z > 5. We find a range of spatial sizes for the CO-traced gas reservoirs up to ∼40 kpc, suggesting that spatially extended cold molecular gas reservoirs may be common in massive, gas-rich galaxies at z ∼ 2. Through CO line stacking, we constrain the gas mass fraction in previously known typical star-forming galaxies at z = 2–3. The stacked CO detection suggests lower molecular gas mass fractions than expected for massive main-sequence galaxies by a factor of ∼3–6. We find total CO line brightness at ∼34 GHz of 0.45 ± 0.2 μK, which constrains future line intensity mapping and CMB experiments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".